Zobrazeno 1 - 10
of 469
pro vyhledávání: '"Stricker, Didier"'
Autor:
Aboukhadra, Ahmed Tawfik, Robertini, Nadia, Malik, Jameel, Elhayek, Ahmed, Reis, Gerd, Stricker, Didier
Surgery monitoring in Mixed Reality (MR) environments has recently received substantial focus due to its importance in image-based decisions, skill assessment, and robot-assisted surgery. Tracking hands and articulated surgical instruments is crucial
Externí odkaz:
http://arxiv.org/abs/2410.01293
Autor:
Sarode, Shalini, Khan, Muhammad Saif Ullah, Shehzadi, Tahira, Stricker, Didier, Afzal, Muhammad Zeshan
We propose ClassroomKD, a novel multi-mentor knowledge distillation framework inspired by classroom environments to enhance knowledge transfer between student and multiple mentors. Unlike traditional methods that rely on fixed mentor-student relation
Externí odkaz:
http://arxiv.org/abs/2409.20237
Autor:
Khan, Muhammad Saif Ullah, Khan, Muhammad Ahmed Ullah, Afzal, Muhammad Zeshan, Stricker, Didier
This paper reformulates cross-dataset human pose estimation as a continual learning task, aiming to integrate new keypoints and pose variations into existing models without losing accuracy on previously learned datasets. We benchmark this formulation
Externí odkaz:
http://arxiv.org/abs/2409.20469
Autor:
Khan, Mohammad Sadil, Sinha, Sankalp, Sheikh, Talha Uddin, Stricker, Didier, Ali, Sk Aziz, Afzal, Muhammad Zeshan
Prototyping complex computer-aided design (CAD) models in modern softwares can be very time-consuming. This is due to the lack of intelligent systems that can quickly generate simpler intermediate parts. We propose Text2CAD, the first AI framework fo
Externí odkaz:
http://arxiv.org/abs/2409.17106
In machining process, 3D reverse engineering of the mechanical system is an integral, highly important, and yet time consuming step to obtain parametric CAD models from 3D scans. Therefore, deep learning-based Scan-to-CAD modeling can offer designers
Externí odkaz:
http://arxiv.org/abs/2409.14087
The novel Dynamic Vision Sensors (DVSs) gained a great amount of attention recently as they are superior compared to RGB cameras in terms of latency, dynamic range and energy consumption. This is particularly of interest for autonomous applications s
Externí odkaz:
http://arxiv.org/abs/2409.11075
Recent studies showcase the competitive accuracy of Vision Transformers (ViTs) in relation to Convolutional Neural Networks (CNNs), along with their remarkable robustness. However, ViTs demand a large amount of data to achieve adequate performance, w
Externí odkaz:
http://arxiv.org/abs/2408.14131
Animating human face images aims to synthesize a desired source identity in a natural-looking way mimicking a driving video's facial movements. In this context, Generative Adversarial Networks have demonstrated remarkable potential in real-time face
Externí odkaz:
http://arxiv.org/abs/2408.13049
The impressive advancements in semi-supervised learning have driven researchers to explore its potential in object detection tasks within the field of computer vision. Semi-Supervised Object Detection (SSOD) leverages a combination of a small labeled
Externí odkaz:
http://arxiv.org/abs/2407.08460
Continual learning (CL) addresses the problem of catastrophic forgetting in neural networks, which occurs when a trained model tends to overwrite previously learned information, when presented with a new task. CL aims to instill the lifelong learning
Externí odkaz:
http://arxiv.org/abs/2407.08411